Predictive Models for Vertical Total Electron Content in Ionosphere
1S.Priya, Assistant Professor, Department of Computer Applications & ISM, Theivanai Ammal College Women, Villupuram (Tamil Nadu), India.
2A.Parameswari, Assistant Professor, Department of Computer Applications & ISM, Theivanai Ammal College Women, Villupuram (Tamil Nadu), India.
Manuscript received on 15 April 2013 | Revised Manuscript received on 22 April 2013 | Manuscript Published on 30 April 2013 | PP: 262-266 | Volume-2 Issue-5, April 2013 | Retrieval Number: E0689042413/13©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The ionosphere is defined as a region of the earth’s upper atmosphere where sufficient ionisation can exist to affect the propagation of radio waves. Prediction of ionosphere vertical total electron content (TEC) are crucial and remain as a challenge for GPS positioning and navigation system , space weather forecast, as well as many other Earth Observation System. TEC is an important descriptive quantity for the ionosphere of the Earth. TEC is strongly affected by solar activity. This ionospheric characteristic constitutes an important parameter in trans ionospheric links since it issued to derive the signal delay imposed by the ionosphere. This paper gives an overview of the various predictive models that can be used to predict Total electron content in ionosphere.
Keywords: K Nearest Neighbor, Linear Predictive Coding, Vertical Total Electron Content.
Scope of the Article: Predictive Analysis